+ j/ `Rt^RIHt^RIHt^RIHt^RIHt^RI H t Rt !RR4t R #) zFContains a logger to push training logs to the Hub, using Tensorboard.)Path)CommitScheduler)EntryNotFoundError) ModelCard) experimentalc|^RIHpV# \d'^RIHpT# \d\R4Rhi;ii;i)zQLoad a SummaryWriter implementation only when an HFSummaryWriter is instantiated. SummaryWriterzvYou must have `tensorboard` installed to use `HFSummaryWriter`. Please run `pip install --upgrade tensorboardX` first.N) tensorboardXr ImportErrortorch.utils.tensorboardrs d/home/luca/screen-checking/.venv/lib/python3.14/site-packages/huggingface_hub/_tensorboard_logger.py_load_summary_writerrs[ .    =   (  s ;7;caa]tRt^'toRt]V3RlV3Rll4tRRR^RRR RR RR RR R RRRRRR/ V3RlRlltV3RlRltV3RlRlt Rt Rt Vt V;t #)HFSummaryWritera Wrapper around the tensorboard's `SummaryWriter` to push training logs to the Hub. Data is logged locally and then pushed to the Hub asynchronously. Pushing data to the Hub is done in a separate thread to avoid blocking the training script. In particular, if the upload fails for any reason (e.g. a connection issue), the main script will not be interrupted. Data is automatically pushed to the Hub every `commit_every` minutes (default to every 5 minutes). > [!WARNING] > `HFSummaryWriter` is experimental. Its API is subject to change in the future without prior notice. Args: repo_id (`str`): The id of the repo to which the logs will be pushed. logdir (`str`, *optional*): The directory where the logs will be written. If not specified, a local directory will be created by the underlying `SummaryWriter` object. commit_every (`int` or `float`, *optional*): The frequency (in minutes) at which the logs will be pushed to the Hub. Defaults to 5 minutes. squash_history (`bool`, *optional*): Whether to squash the history of the repo after each commit. Defaults to `False`. Squashing commits is useful to avoid degraded performances on the repo when it grows too large. repo_type (`str`, *optional*): The type of the repo to which the logs will be pushed. Defaults to "model". repo_revision (`str`, *optional*): The revision of the repo to which the logs will be pushed. Defaults to "main". repo_private (`bool`, *optional*): Whether to make the repo private. If `None` (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists. path_in_repo (`str`, *optional*): The path to the folder in the repo where the logs will be pushed. Defaults to "tensorboard/". repo_allow_patterns (`list[str]` or `str`, *optional*): A list of patterns to include in the upload. Defaults to `"*.tfevents.*"`. Check out the [upload guide](https://huggingface.co/docs/huggingface_hub/guides/upload#upload-a-folder) for more details. repo_ignore_patterns (`list[str]` or `str`, *optional*): A list of patterns to exclude in the upload. Check out the [upload guide](https://huggingface.co/docs/huggingface_hub/guides/upload#upload-a-folder) for more details. token (`str`, *optional*): Authentication token. Will default to the stored token. See https://huggingface.co/settings/token for more details kwargs: Additional keyword arguments passed to `SummaryWriter`. Examples: ```diff # Taken from https://pytorch.org/docs/stable/tensorboard.html - from torch.utils.tensorboard import SummaryWriter + from huggingface_hub import HFSummaryWriter import numpy as np - writer = SummaryWriter() + writer = HFSummaryWriter(repo_id="username/my-trained-model") for n_iter in range(100): writer.add_scalar('Loss/train', np.random.random(), n_iter) writer.add_scalar('Loss/test', np.random.random(), n_iter) writer.add_scalar('Accuracy/train', np.random.random(), n_iter) writer.add_scalar('Accuracy/test', np.random.random(), n_iter) ``` ```py >>> from huggingface_hub import HFSummaryWriter # Logs are automatically pushed every 15 minutes (5 by default) + when exiting the context manager >>> with HFSummaryWriter(repo_id="test_hf_logger", commit_every=15) as logger: ... logger.add_scalar("a", 1) ... logger.add_scalar("b", 2) ``` c<V^8dQhRR/#returnr)format __classdict__s"r __annotate__HFSummaryWriter.__annotate__os$$):$c"<\SV`V4#N)super__new__)clsargskwargs __class__s&*,r rHFSummaryWriter.__new__nsws##rlogdirN commit_everysquash_historyF repo_type repo_revision repo_private path_in_repo tensorboardrepo_allow_patternsz *.tfevents.*repo_ignore_patternstokenc<V^8dQhRS[RS[R,RS[S[,RS[RS[R,RS[R,RS[R,R S[R,R S[S[,S[,R,R S[S[,S[,R,R S[R,/ #) rrepo_idr$Nr%r&r'r(r)r*r,r-r.)strintfloatboollist)rrs"r rrrs;M;M;Md ;M Ek ;M  ;M:;MTz;MTk;MDj;M"#Y_t3;M#3i#o4;MTz;Mrc  *\4!R RV/V BVnVPPVn\VP\4'g0\ RVP R\ VP4 R24hVeVR8Xd!\VP4PpM>$,,$..YDyy}}VR( d * KK+ , $IIf    T\\T^^  L +" !R=D !s ,G99HHc <V^8dQhRS[/#)rrF)r1)rrs"r rrs333rc .\VPV4#)z;Forward the SummaryWriter API to the lazily-created writer.)getattrrB)rNrFs&&r __getattr__HFSummaryWriter.__getattr__st++T22rc<V^8dQhRR/#rr)rrs"r rrs,rc:VPP4V#r)rB __enter__)rNs&r rYHFSummaryWriter.__enter__s &&( rc VPPWV4VPP4pVP 4R#)zLPush to hub in a non-blocking way when exiting the logger's context manager.N)rB__exit__rHtriggerresult)rNexc_typeexc_valexc_tbfutures&&&& r r\HFSummaryWriter.__exit__s3 %%h@'') r)rBr$r0r(r'rH)__name__ __module__ __qualname____firstlineno____doc__rrrPrUrYr\__static_attributes____classdictcell__ __classcell__)r"rs@@r rr'sDL$$$;M" ;M %& ;M % ;M!%;M%);M%);M$1;M7E;M8<;M!;M;Mz33rrN) rhpathlibr_commit_schedulerrerrorsrrepocardrutilsrrrrrr rqs+M.& TTr